Data Reliability Engineer

Overview

Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries together.

 

We're looking for a Data Reliability Engineer to keep our trading and data platforms running seamlessly. You'll be a guardian of the Python data pipelines and the scheduled start- and end-of-day jobs our trading desks depend on, making sure these trading-critical workflows run on time and with precision. In equal measure you'll work hands-on with the data: onboarding new datasets, reconciling and validating them, and tracing anomalies back to their source. When something breaks you'll dive in, diagnose quickly, and make the fix that keeps downstream systems healthy.

You'll work across a layered platform: an ingestion layer that decodes incoming feeds into structured data, a data-flow framework that streams and transforms it, configuration-driven feeds and analytical applications built on top, scheduled batch jobs that assemble each day's start- and end-of-day datasets, and a serving layer that delivers it all to trading tools. Across every layer you'll work alongside quantitative researchers, developers, and traders, as well as other reliability engineers on the team and partner teams such as those in reference and market data, to review changes, manage releases, and continually strengthen both the pipelines and the data flowing through them.

In this role you will:

• Engineer - Build and maintain the tooling that brings new data sources onto the platform, turning ad-hoc data handling into dependable, automated workflows in Python.
• Analyse - Get to know the data inside out, validate and reconcile it against expectations, and help researchers get it into the shape their models need.
• Investigate - When a derived dataset looks wrong, chase the discrepancy upstream until you find the root cause, combining detective work, technical analysis, and the right conversations across teams.
• Support - Provide proactive oversight of trading-critical scheduled jobs and Python pipelines, keeping them on time and within SLA; triage, troubleshoot, and resolve incidents under tight turnaround, validating downstream impact and keeping recovery procedures ready.
• Release - Own safe delivery to production - review configuration and code changes, enforce safe deployment standards, and coordinate risk-aware releases through GitLab and Octopus Deploy.

 

What we’re looking for

• 2+ years in a data engineering, data science, or production-support role, or a degree in a technical or data discipline.
• Demonstrated experience with Python (or a comparable language).
• Experience with at least one SQL variant (PostgreSQL, MSSQL, MySQL), and the ability to pick up others as needed.
• Strong analytical and troubleshooting skills; detail-oriented, self-motivated, and curious.
• Willingness to work shifts: the team works an alternating weekday early/late shift rotation, with participation in an on-call rota.
• Exposure to change-management and incident-management practices.
• Comfort with technical documentation and handling support cases.
• Comfortable working in both Windows and Linux environments.

If you're a recruiting agency and want to partner with us, please reach out to [email protected]. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.